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build-paths-advanced

Scaffold an agent system where Oracle AI DB is the *only* state store, composed from the build-paths/skills/ building-block library. Stack — langchain-oracledb + oracle-database-mcp-server + in-DB ONNX embeddings + OCI GenAI Grok 4 + Open WebUI. Three projects — production-feeling NL2SQL+RAG hybrid analyst, self-improving research agent, conversational schema designer. For users who want a real DB-as-only-store agent demo.

58

Quality

68%

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SecuritybySnyk

Passed

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tessl review fix ./build-paths/advanced/SKILL.md
SKILL.md
Quality
Evals
Security

Quality

Content

73%Weight 40%Scale 1-5

Reviews the quality of instructions and guidance provided to agents. Good implementation is clear, handles edge cases, and produces reliable results.

The body is a well-structured, highly actionable workflow with strong validation and recovery loops, clearly composed from named building-block skills. Its weaknesses are length/density and some per-idea detail that could be split into separate reference files for cleaner progressive disclosure.

Suggestions

Move the per-idea memory/app-code breakdowns (Ideas 1–3) and their code skeletons into separate reference files, keeping the main body as an orchestration overview.

Trim the dev-reset SQL + OAMP reset block into a referenced snippet or script rather than inlining the full block.

Consider pulling the planner system-prompt rules and max_tokens rationale into a shared reference to reduce main-body density.

DimensionReasoningScore

Conciseness

The body is information-dense and avoids teaching concepts Claude already knows, but it is long and dense enough that several inlined tables and per-idea code blocks (e.g. the planner skeleton, the reset SQL/OAMP blocks) could be tightened or moved to references.

3 / 5

Actionability

It provides concrete, executable guidance — exact CLI commands (onnx2oracle load ...), real SQL, a runnable planner skeleton, and specific verify.py checks — with only minor gaps where ~80 LOC targets are described rather than shown.

4 / 5

Workflow Clarity

Steps 0–5 are clearly sequenced with explicit validation checkpoints (verify.py forbidden-imports grep, OAMP cold→warm round-trip, 'Wait for y' confirmation, max-3-retry recovery loop), plus a dedicated Stop conditions and 'What you must NOT do' checklist for the destructive/batch operations.

5 / 5

Progressive Disclosure

Step 0 lists real one-level-deep references (skills/* SKILL.md files, shared/references/oamp.md, project-ideas.md) with clear pointers, but the body still inlines substantial per-idea detail and code that could live in separate idea-specific reference files.

4 / 5

Total

16

/

20

Passed

Description

62%Weight 40%Scale 1-5

Based on the skill's description, can an agent find and select it at the right time? Clear, specific descriptions lead to better discovery.

The description is highly specific and distinctive, naming a precise stack and the DB-as-only-store constraint that separates it from related skills. Its main weakness is the missing explicit 'Use when...' trigger clause and a lack of natural-language keywords users would actually say.

Suggestions

Add an explicit 'Use when...' trigger clause, e.g. 'Use when the user wants a DB-as-only-store agent demo built on Oracle AI DB.'

Include natural trigger terms users would actually say (e.g. 'Oracle agent', 'NL2SQL demo', 'DB-only state store') alongside the stack jargon.

Convert the stack list into a tighter one-line summary to reduce density without losing distinctiveness.

DimensionReasoningScore

Specificity

Lists several concrete actions — scaffold an agent system, compose from a building-block library, and names three specific project types (NL2SQL+RAG analyst, research agent, schema designer) plus the exact stack components, with only minor coverage gaps around what scaffolding concretely emits.

4 / 5

Completeness

It clearly answers 'what' (scaffold an Oracle-DB-as-only-store agent system with a named stack and three project options), but the 'when' is only weakly implied by 'For users who want a real DB-as-only-store agent demo' rather than an explicit 'Use when...' trigger clause.

3 / 5

Trigger Term Quality

It is rich in technical stack terminology (Oracle AI DB, langchain-oracledb, ONNX, OCI GenAI Grok 4) but lacks the natural everyday phrases a user would actually say when they need this skill, and offers no synonyms or common variations of those triggers.

3 / 5

Distinctiveness Conflict Risk

The constraint 'Oracle AI DB is the only state store' plus the specific stack (langchain-oracledb + oracle-database-mcp-server + in-DB ONNX + OCI GenAI Grok 4) carves a clear niche with minimal overlap risk against other skills.

5 / 5

Total

15

/

20

Passed

Validation

87%

Checks the skill against the spec for correct structure and formatting. All validation checks must pass before discovery and implementation can be scored.

Validation14 / 16 Passed

Validation for skill structure

CriteriaDescriptionResult

frontmatter_unknown_keys

Unknown frontmatter key(s) found; consider removing or moving to metadata

Warning

referenced_paths_exist

Referenced path issues: 2 missing

Warning

Total

14

/

16

Passed

Repository
oracle-devrel/oracle-ai-developer-hub
Reviewed

Table of Contents

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